GenGeo

Inspiration

People and businesses frequently make important and expensive decisions about locations using incomplete or fragmented information. When someone moves to a new neighborhood or considers opening a business, they must evaluate many factors such as safety, school quality, demographics, nearby businesses, housing prices, public transportation, and economic growth.

However, this information is scattered across many platforms. People often rely on Google Maps reviews, census data, school rankings, crime statistics, local news articles, Reddit discussions, zoning maps, demographic reports, economic data, and real estate listings to understand a single area.

Because this information is distributed across multiple sources, it is time-consuming and difficult to interpret. Individuals and businesses may spend hours or even days researching different websites just to gain a basic understanding of a neighborhood.

Research also suggests that approximately 65% of people are visual learners Despite this, most geographic information today is presented through text-heavy reports or fragmented datasets rather than visual spatial tools.

This inspired us to build GenGeo, a platform designed to transform scattered geographic information into clear, visual, and AI-generated insights about places.

What it does

GenGeo is a map-based AI platform that analyzes geographic areas and summarizes information about them in plain language.

Users enter a location, choose a search radius (for example 1 km or 5 km), and select the parameters they care about such as safety, schools, demographics, housing costs, nearby businesses, or public transportation.

Users can ask questions such as:

Is this neighborhood safe?
Are there good schools nearby?
What types of people live in this area?
Is this a good location to open a restaurant or café?
Is this neighborhood growing or declining?

The system collects data from multiple sources and synthesizes it using AI to generate clear, readable summaries about the characteristics of a location.

How we built it

GenGeo is built as a map-centered intelligence platform combining geographic data with AI analysis. We used OpenStreetMap and Google Maps API.

Challenges we ran into

One major challenge was combining multiple geographic datasets.

Different sources often use different formats, coordinate systems, and update frequencies. Integrating these datasets required normalization so they could be analyzed together.

Another challenge was balancing data complexity with usability. Many location intelligence tools overwhelm users with too many metrics. We focused on summarizing the most important signals so users could quickly understand a location.

We also encountered API rate limits and inconsistent data responses, which required error handling and fallback logic to maintain system reliability.

Finally, designing effective AI summaries required experimenting with prompt engineering and data structuring to ensure outputs were both accurate and useful.

Accomplishments that we're proud of

One accomplishment we are proud of is successfully creating a system that aggregates multiple sources of geographic data and converts them into understandable insights.

We built a working prototype that allows users to:

search locations
define geographic analysis areas
retrieve location-based datasets
generate AI summaries about neighborhoods

Most importantly, the platform demonstrates how complex geographic data can be translated into simple explanations that help people make decisions.